A novel microbiome metabolic modulator improves the growth performance of broiler chickens in multiple trials and modulates targeted energy and amino acid metabolic pathways in the cecal metagenome.

A meta-analysis of 19 floor-pen trials (579 replicate pen observations) in diverse geographies, basal diets, seasons, and medication programs was carried out to evaluate the effects of 2 precision glycan microbiome metabolic modulators (MMM1 and MMM2) on the performance of broiler chickens. In each trial, negative-control (NC) diets were compared with either MMM1 (14 trials) or MMM2 (8 trials), supplemented at an intended dose of 500 g/MT from hatch to 31 to 42 d. A dose response of MMM2 was evaluated in 8 trials at doses of 100, 250, 500, and 1,000 g/MT, not all present in each trial. Linear mixed-effect models were constructed for the final BW, cumulative feed intake, feed conversion ratio (FCR) corrected by mortality and BW (cFCR), and mortality, with Treatment as the fixed effect, nested random effects of Trial and Block, and adjustments for heterogeneity of variances. A significance level of P < 0.05 was used. In one of the studies, cecal content samples were collected at 42 d for analysis of microbiome gene abundance. Microbiome metabolic modulator 2 exhibited a reduction of the cFCR of 0.06 g feed/g BW gain compared with the NC and 0.03 g feed/g BW gain compared with MMM1, whereas MMM1 reduced the cFCR by 0.03 g feed/g BW gain compared with NC. Both MMM1 and MMM2 increased the final BW compared with the NC by 43 and 48 g/bird, respectively, with no difference among them. Compared with NC, feed intake was increased by MMM1 (+51 g/bird) and reduced by MMM2 (-74 g/bird). A one-directional dose response of the MMM2 ingredient was observed for the final BW (increasing) and cFCR (decreasing), whereas the feed intake response reached a minimum at 500 g/MT. The metagenomic analysis confirmed an increase in the abundance of genes belonging to the acrylate pathway, which is involved in propionate production, as well as arginine-N-succinyl transferase which is involved in the catabolism of arginine, in response to MMM2. Differential glycan structures of the MMM had an impact on the size and consistency of performance effects in broilers.

Time course of neuromuscular adaptations to knee extensor eccentric training.

This study investigated the chronology of neural and morphological adaptations to knee extensor eccentric training and their contribution to strength gains in isometric, concentric and eccentric muscle actions. 20 male healthy subjects performed a 12-week eccentric training program on an isokinetic dynamometer, and neuromuscular evaluations of knee extensors were performed every 4 weeks. After 12 training weeks, significant increases were observed for: isometric (24%), concentric (15%) and eccentric (29%) torques; isometric (29%) and eccentric (33%) electromyographic activity; muscle thickness (10%) and anatomical cross-sectional area (19%). Eccentric and isometric torques increased progressively until the end of the program. Concentric torque and muscle mass parameters increased until the eighth training week, but did not change from this point to the twelfth training week. Eccentric and isometric activation increased at 4 and 8 training weeks, respectively, while no change was found in concentric activation. These results suggest that: 1) the relative increment in concentric strength was minor and does not relate to neural effects; 2) eccentric and isometric strength gains up to 8 training weeks are explained by the increased neural activation and muscle mass, whereas the increments in the last 4 training weeks seem to be associated with other mechanisms.

Optical coherent state discrimination using a closed-loop quantum measurement.

Quantum mechanics hinders our ability to determine the state of a physical system in two ways: individual measurements provide only partial information about the observed system (because of Heisenberg uncertainty), and measurements are themselves invasive-meaning that little or no refinement is achieved by further observation of an already measured system. Theoretical methods have been developed to maximize the information gained from a quantum measurement while also minimizing disturbance, but laboratory implementation of optimal measurement procedures is often difficult. The standard class of operations considered in quantum information theory tends to rely on superposition-basis and entangled measurements, which require high-fidelity implementation to be effective in the laboratory. Here we demonstrate that real-time quantum feedback can be used in place of a delicate quantum superposition, often called a 'Schrödinger cat state', to implement an optimal quantum measurement for discriminating between optical coherent states. Our procedure actively manipulates the target system during the measurement process, and uses quantum feedback to modify the statistics of an otherwise sub-optimal operator to emulate the optimal cat-state measurement. We verify a long-standing theoretical prediction and demonstrate feedback-mediated quantum measurement at its fundamental quantum limit over a non-trivial region of parameter space.

Generalized limits for single-parameter quantum estimation.

We develop generalized bounds for quantum single-parameter estimation problems for which the coupling to the parameter is described by intrinsic multisystem interactions. For a Hamiltonian with k-system parameter-sensitive terms, the quantum limit scales as 1/Nk, where N is the number of systems. These quantum limits remain valid when the Hamiltonian is augmented by any parameter-independent interaction among the systems and when adaptive measurements via parameter-independent coupling to ancillas are allowed.

Deterministic and nondestructively verifiable preparation of photon number states.

An experimentally viable approach for preparing arbitrary photon number states of a cavity mode using continuous measurement and real-time quantum feedback is presented. The procedure passively monitors the number state actually achieved in each feedback-stabilized measurement trajectory, thus providing nondestructively verifiable photon generation. The feasibility of a possible cavity QED implementation in the many-atom, good-cavity-coupling regime is analyzed.

Suppression of spin projection noise in broadband atomic magnetometry.

We demonstrate that quantum nondemolition measurement, combined with a suitable parameter estimation procedure, can improve the sensitivity of a broadband atomic magnetometer by reducing uncertainty due to spin projection noise. Furthermore, we provide evidence that real-time quantum feedback control offers robustness to classical uncertainties, including shot-to-shot atom number fluctuations, that would otherwise prevent quantum-limited performance.

Efficient chemical kinetic modeling through neural network maps.

An approach to modeling nonlinear chemical kinetics using neural networks is introduced. It is found that neural networks based on a simple multivariate polynomial architecture are useful in approximating a wide variety of chemical kinetic systems. The accuracy and efficiency of these ridge polynomial networks (RPNs) are demonstrated by modeling the kinetics of H(2) bromination, formaldehyde oxidation, and H(2)+O(2) combustion. RPN kinetic modeling has a broad range of applications, including kinetic parameter inversion, simulation of reactor dynamics, and atmospheric modeling.

Real-time quantum feedback control of atomic spin-squeezing.

Real-time feedback performed during a quantum nondemolition measurement of atomic spin-angular momentum allowed us to influence the quantum statistics of the measurement outcome. We showed that it is possible to harness measurement backaction as a form of actuation in quantum control, and thus we describe a valuable tool for quantum information science. Our feedback-mediated procedure generates spin-squeezing, for which the reduction in quantum uncertainty and resulting atomic entanglement are not conditioned on the measurement outcome.

Quantum Kalman filtering and the Heisenberg limit in atomic magnetometry.

The shot-noise detection limit in current high-precision magnetometry [Nature (London) 422, 596 (2003)] is a manifestation of quantum fluctuations that scale as 1/sqrt[N] in an ensemble of N atoms. Here, we develop a procedure that combines continuous measurement and quantum Kalman filtering [Rep. Math. Phys. 43, 405 (1999)]] to surpass this conventional limit by exploiting conditional spin squeezing to achieve 1/N field sensitivity. Our analysis demonstrates the importance of optimal estimation for high bandwidth precision magnetometry at the Heisenberg limit and also identifies an approximate estimator based on linear regression.

Optimal identification of Hamiltonian information by closed-loop laser control of quantum systems.

A closed loop learning control concept is introduced for teaching lasers to manipulate quantum systems for the purpose of optimally identifying Hamiltonian information. The closed loop optimal identification algorithm operates by revealing the distribution of Hamiltonians consistent with the data. The control laser is guided to perform additional experiments, based on minimizing the dispersion of the distribution. Operation of such an apparatus is simulated for two model finite dimensional quantum systems.

Inverse-problem approach to designing photonic crystals for cavity QED experiments.

Photonic band gap (PBG) materials are attractive for cavity QED experiments because they provide extremely small mode volumes and are monolithic, integratable structures. As such, PBG cavities are a promising alternative to Fabry-Perot resonators. However, the cavity requirements imposed by QED experiments, such as the need for high Q (low cavity damping) and small mode volumes, present significant design challenges for photonic band gap materials. Here, we pose the PBG design problem as a mathematical inversion and provide an analytical solution for a two-dimensional (2D) crystal. We then address a planar (2D crystal with finite thickness) structure using numerical techniques.